Spatial trace element variations of stibnite in a world-class Sb deposit and their implications for ore genesis and exploration
Bibliographic record
Abstract
Abstract Stibnite samples collected from various depths in the world-class Xikuangshan Sb deposit in south China were analyzed to determine their trace element signatures and identify features that could be used in the exploration for similar deposits elsewhere. In situ LA-ICP-MS analyses revealed that trace elements such as Cu, Tl, Pb, and Hg are incorporated into the stibnite structure through complex substitution mechanisms. These include substitutions such as (Cu+ + Tl+) + (Pb2+ + Hg2+) ↔ 2Sb3+ + 2□ and Cu+ + Fe2+/Zn2+↔ Sb3+ + □, where ρ denotes vacancies in the stibnite lattice. A key finding of the analyses is that the As, Zn, and Tl contents of the stibnite vary systematically with depth in the deposit, such that the concentrations of As and Tl gradually increase with depth, whereas the Zn concentration decreases. These depth-related trends are interpreted to reflect the migration pathway of ore-forming fluids and the temperature evolution of the hydrothermal system. We therefore propose that these trace elements and their ratios (Tl/Zn and As/Zn) can serve to reconstruct the pathways of ore-fluid migration and target the exploration for orebodies. In addition to our data for the Xikuangshan Sb deposit, we have compiled published data on the trace element compositions of stibnite from Sb, Sb-W, Au-Sb-W, and Au ore systems worldwide. The results show that Cu, Pb, Se, As, and Ag+Sn+In in stibnite can be used to distinguish metal associations in natural hydrothermal ore systems. This study demonstrates that in situ LA-ICP-MS trace element analysis of stibnite has the potential to be used to fingerprint fluid flow paths and to provide a new tool for exploration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".